THE POTENTIAL OF INDONESIAN MARINE NATURAL PRODUCT WITH DUAL TARGETING ACTIVITY THROUGH SARS-COV-2 3CLPRO AND PLPRO: AN IN SILICO STUDIES

CIKAL FIARSI NAHIR; MASTERIA YUNOVILSA PUTRA; JOKO TRI WIBOWO; VANNAJAN SANGHIRAN LEE; ARRY YANUAR

doi:10.22159/ijap.2023v15i5.48416

Authors

CIKAL FIARSI NAHIR Laboratory of Biomedical Computation and Drug Design, Faculty of Pharmacy, Universitas Indonesia, Depok, Jawa Barat-16424, Indonesia https://orcid.org/0000-0003-1280-755X
MASTERIA YUNOVILSA PUTRA Research Center for Vaccine and Drug, National Research and Innovation Agency, Bogor, Jawa Barat, Indonesia. National Metabolomics Collaborative Research Center, Faculty of Pharmacy, Universitas Indonesia, Kampus UI Depok, West Java-16424, Indonesia
JOKO TRI WIBOWO Research Center for Vaccine and Drug, National Research and Innovation Agency, Bogor, Jawa Barat, Indonesia https://orcid.org/0000-0003-3467-6263
VANNAJAN SANGHIRAN LEE Department of Chemistry, Faculty of Science, University of Malaya, Kuala Lumpur, Malaysia
ARRY YANUAR Laboratory of Biomedical Computation and Drug Design, Faculty of Pharmacy, Universitas Indonesia, Depok, Jawa Barat-16424, Indonesia. National Metabolomics Collaborative Research Center, Faculty of Pharmacy, Universitas Indonesia, Kampus UI Depok, West Java-16424, Indonesia

DOI:

https://doi.org/10.22159/ijap.2023v15i5.48416

Keywords:

Marine Natural Products, In Silico, SARS-CoV-2, 3CLpro, PLpro, Virtual Screening, ADMET Prediction, Molecular Docking, Molecular Dynamic

Abstract

Objective: This research was conducted to find potential candidate compounds from one hundred thirty-seven Indonesian marine natural products capable of preventing SARS-CoV-2 with a computational approach.

Methods: The physicochemical properties and Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) profile of compounds were predicted using ADMETLab. The candidate compounds were filtered using AutodockVina. Molecular docking was carried out using AutoDockTools on the SARS-CoV-2 3-Chymotrypsin-like protease (3CLpro) and Papain-like protease (PLpro) that is essential for the SARS-CoV-2 life cycle. Also, AMBER22 was used to perform molecular dynamics simulations in this study.

Results: Based on molecular docking results, Pre-Neo-Kaluamine has good activity against 3CLpro with a bond energy value of-10.35 kcal/mol. Cortistatin F showed excellent binding activity on PLpro, with energy value results of-10.62 kcal/mol. Acanthomanzamine C has dual targeting activity and interacts well with protein 3CLpro and PLpro with binding energy values ranging from 10 kcal/mol to 14 kcal/mol.

Conclusion: The molecular docking results were corroborated by molecular dynamics simulation results and showed good stability of the candidate ligands, and we found that there were three potential compounds as protease inhibitors of SARS-CoV-2 including Pre-Neo-Kaluamine for 3CLpro, Cortistatin F for PLpro, and Acanthomanzamine C which had dual targeting activity against both proteases.

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